Short Time Scales Research Articles

Atypical intrinsic neural timescale in the left angular gyrus in Alzheimer's disease.

Alzheimer's disease is characterized by cognitive impairment and progressive brain atrophy. Recent human neuroimaging studies reported atypical anatomical and functional changes in some regions in the default mode network in patients with Alzheimer's disease, but which brain area of the default mode network is the key region whose atrophy disturbs the entire network activity and consequently contributes to the symptoms of the disease remains unidentified. Here, in this case-control study, we aimed to identify crucial neural regions that mediated the phenotype of Alzheimer's disease, and as such, we examined the intrinsic neural timescales-a functional metric to evaluate the capacity to integrate diverse neural information-and grey matter volume of the regions in the default mode network using resting-state functional MRI images and structural MRI data obtained from individuals with Alzheimer's disease and cognitively typical people. After confirming the atypically short neural timescale of the entire default mode network in Alzheimer's disease and its link with the symptoms of the disease, we found that the shortened neural timescale of the default mode network was associated with the aberrantly short neural timescale of the left angular gyrus. Moreover, we revealed that the shortened neural timescale of the angular gyrus was correlated with the atypically reduced grey matter volume of this parietal region. Furthermore, we identified an association between the neural structure, brain function and symptoms and proposed a model in which the reduced grey matter volume of the left angular gyrus shortened the intrinsic neural time of the region, which then destabilized the entire neural timescale of the default mode network and resultantly contributed to cognitive decline in Alzheimer's disease. These findings highlight the key role of the left angular gyrus in the anatomical and functional aetiology of Alzheimer's disease.

Corticosterone exposure is associated with long-term changes in DNA methylation, physiology and breeding decisions in a wild bird.

When facing challenges, vertebrates activate a hormonal stress response that can dramatically alter behaviour and physiology. Although this response can be costly, conceptual models suggest that it can also recalibrate the stress response system, priming more effective responses to future challenges. Little is known about whether this process occurs in wild animals, particularly in adulthood, and if so, how information about prior experience with stressors is encoded. One potential mechanism is hormonally mediated changes in DNA methylation. We simulated the spikes in corticosterone that accompany a stress response using non-invasive dosing in tree swallows (Tachycineta bicolor) and monitored the phenotypic effects 1 year later. In a subset of individuals, we characterized DNA methylation using reduced representation bisulfite sequencing shortly after treatment and a year later. The year after treatment, experimental females had stronger negative feedback and initiated breeding earlier-traits that are associated with stress resilience and reproductive performance in our population-and higher baseline corticosterone. We also found that natural variation in corticosterone predicted patterns of DNA methylation. Finally, corticosterone treatment influenced methylation on short (1-2 weeks) and long (1 year) time scales; however, these changes did not have clear links to functional regulation of the stress response. Taken together, our results are consistent with corticosterone-induced priming of future stress resilience and support DNA methylation as a potential mechanism, but more work is needed to demonstrate functional consequences. Uncovering the mechanisms linking experience with the response to future challenges has implications for understanding the drivers of stress resilience.

Blade-Coating of High Crystallinity Cesium-Formamidinium Perovskite Formulations.

Up-scalable coating processes need to be developed to manufacture efficient and stable perovskite-based solar modules. In this work, we combine two Lewis base additives (N,N'-dimethylpropyleneurea and thiourea) to fabricate high-quality Cs0.15FA0.85PbI3 perovskite films by blade-coating on large areas. Selected-area electron diffraction patterns reveal a minimization of stacking faults in the α-FAPbI3 phase for this specific cesium-formamidinium composition in both spin-coated and blade-coated perovskite films, demonstrating its scaling potential. The underlying mechanism of the crystallization process and the specific role of thiourea are characterized by Fourier transform infrared spectroscopy and in situ optical absorption, showing clear interaction between thiourea and perovskite precursors and halved film-formation activation energy (from 114 to 49 kJ/mol), which contribute to the obtained specific morphology with the formation of large domain sizes on a short time scale. The blade-coated perovskite solar cells demonstrate a maximum efficiency of approximately 16.9% on an aperture area of 1 cm2.

Phylogenetic indices and temporal and spatial scales shape the neighborhood effect on seedling survival in a mid-mountain moist evergreen broad-leaved forest, Gaoligong Mountains, Southwestern China.

Density dependence and habitat filtering have been proposed to aid in understanding community assembly and species coexistence. Phylogenetic relatedness between neighbors was used as a proxy for assessing the degree of ecological similarity among species. There are different conclusions regarding the neighborhood effect in previous studies with different phylogenetic indices or at different spatiotemporal scales. However, the effects of density dependence, neighbor phylogenetic relatedness, and habitat filtering on seedling survival with different phylogenetic indices or at different temporal and spatial scales are poorly understood. We monitored 916 seedlings representing 56 woody plant species within a 4-ha forest dynamics plot for 4 years (from 2020 to 2023) in a subtropical mid-mountain moist evergreen broad-leaved forest in the Gaoligong Mountains, Southwestern China. Using generalized linear mixed models, we tested whether and how four phylogenetic indices: total phylogenetic distance (TOTPd), average phylogenetic distance (AVEPd), relative average phylogenetic distance (APd'), and relative nearest taxon phylogenetic distance (NTPd'), three temporals (1, 2, and 3 years), and spatial scales (1, 2, and 4 ha) affect the effect of density dependence, phylogenetic density dependence, and habitat filtering on seedling survival. We found evidence of the effect of phylogenetic density dependence in the 4-ha forest dynamics plot. The effects of density dependence, phylogenetic density dependence, and habitat filtering on seedling survival were influenced by phylogenetic indices and temporal and spatial scales. The effects of phylogenetic density dependence and habitat filtering on seedling survival were more conspicuous only at 1-year intervals, compared with those at 2- and 3-year intervals. We did not detect any effects of neighborhood or habitat factors on seedling survival at small scales (1 and 2 ha), although these effects were more evident at the largest spatial scale (4 ha). These findings highlight that the effects of local neighborhoods and habitats on seedling survival are affected by phylogenetic indices as well as temporal and spatial scales. Our study suggested that phylogenetic index APd', shortest time scale (1 year), and largest spatial scales (4 ha) were suitable for neighborhood studies in a mid-mountain moist evergreen broad-leaved forest in Gaoligong Mountains. Phylogenetic indices and spatiotemporal scales have important impacts on the results of the neighborhood studies.

ALMA-IMF

Context. The star formation process leads to an increased chemical complexity in the interstellar medium. Sites associated with high-mass star and cluster formation exhibit a so-called hot core phase, characterized by high temperatures and column densities of complex organic molecules. Aims. We aim to systematically search for and identify a sample of hot cores toward the 15 Galactic protoclusters of the ALMA-IMF Large Program and investigate their statistical properties. Methods. We built a comprehensive census of hot core candidates toward the ALMA-IMF protoclusters based on the detection of two CH3OCHO emission lines at 216.1 GHz. We used the source extraction algorithm GExt2D to identify peaks of methyl formate (CH3OCHO) emission, a complex species commonly observed toward sites of star formation. We performed a cross-matching with the catalog of thermal dust continuum sources from the ALMA-IMF 1.3 mm continuum data to infer their physical properties. Results. We built a catalog of 76 hot core candidates with masses ranging from ~0.2 M⊙ to ~80 M⊙, of which 56 are new detections. A large majority of these objects, identified from methyl formate emission, are compact and rather circular, with deconvolved full width at half maximum (FWHM) sizes of ~2300 au on average. The central sources of two target fields show more extended, but still rather circular, methyl formate emission with deconvolved FWHM sizes of ~6700 au and 13 400 au. About 30% of our sample of methyl formate sources have core masses above 8 M⊙ and range in size from ~1000 au to 13 400 au, which is in line with measurements of archetypical hot cores. The origin of the CH3OCHO emission toward the lower-mass cores may be explained as a mixture of contributions from shocks or may correspond to objects in a more evolved state (i.e., beyond the hot core stage). We find that the fraction of hot core candidates increases with the core mass, suggesting that the brightest dust cores are all in the hot core phase. Conclusions. Our results suggest that most of these compact methyl formate sources are readily explained by simple symmetric models, while collective effects from radiative heating and shocks from compact protoclusters are needed to explain the observed extended CH3OCHO emission. The large fraction of hot core candidates toward the most massive cores suggests that they rapidly enter the hot core phase and that feedback effects from the forming protostar(s) impact their environment on short timescales.

Disentangling Carbon Concentration Changes Along Pathways of North Atlantic Subtropical Mode Water

AbstractNorth Atlantic subtropical mode water (NASTMW) serves as a major conduit for dissolved carbon to penetrate into the ocean interior by its wintertime outcropping events. Prior research on NASTMW has concentrated on its physical formation and destruction, as well as Lagrangian pathways and timescales of water into and out of NASTMW. In this study, we examine how dissolved inorganic carbon (DIC) concentrations are modified along Lagrangian pathways of NASTMW on subannual timescales. We introduce Lagrangian parcels into a physical‐biogeochemical model and release these parcels annually over two decades. For different pathways into, out of, and within NASTMW, we calculate changes in DIC concentrations along the path (ΔDIC), distinguishing contributions from vertical mixing and biogeochemical processes. The strongest ΔDIC is during subduction of water parcels (+101 μmol L−1 in 1 year), followed by transport out of NASTMW due to increases in density in water parcels (+10 μmol L−1). While the mean ΔDIC for parcels that persist within NASTMW in 1 year is relatively small at +6 μmol L−1, this masks underlying dynamics: individual parcels undergo interspersed DIC depletion and enrichment, spanning several timescales and magnitudes. Most DIC enrichment and depletion regimes span timescales of weeks, related to phytoplankton blooms. However, mixing and biogeochemical processes often oppose one another at short timescales, so the largest net DIC changes occur at timescales of more than 30 days. Our new Lagrangian approach complements bulk Eulerian approaches, which average out this underlying complexity, and is relevant to other biogeochemical studies, for example, on marine carbon dioxide removal.

Role of the Locus Coeruleus Arousal Promoting Neurons in Maintaining Brain Criticality across the Sleep-Wake Cycle.

Sleep control depends on a delicate interplay among brain regions. This generates a complex temporal architecture with numerous sleep-stage transitions and intermittent fluctuations to micro-states and brief arousals. These temporal dynamics exhibit hallmarks of criticality, suggesting that tuning to criticality is essential for spontaneous sleep-stage and arousal transitions. However, how the brain maintains criticality remains not understood. Here, we investigate θ- and δ-burst dynamics during the sleep-wake cycle of rats (Sprague-Dawley, adult male) with lesion in the wake-promoting locus coeruleus (LC). We show that, in control rats, θ- and δ-bursts exhibit power-law (θ-bursts, active phase) and exponential-like (δ-bursts, quiescent phase) duration distributions, as well as power-law long-range temporal correlations (LRTCs)-typical of non-equilibrium systems self-organizing at criticality. Furthermore, consecutive θ- and δ-bursts durations are characterized by anti-correlated coupling, indicating a new class of self-organized criticality that emerges from underlying feedback between neuronal populations and brain areas involved in generating arousals and sleep states. In contrast, we uncover that LC lesion leads to alteration of θ- and δ-burst critical features, with change in duration distributions and correlation properties, and increase in θ-δ coupling. Notably, these LC-lesion effects are opposite to those observed for lesions in the sleep-promoting ventrolateral preoptic (VLPO) nucleus. Our findings indicate that critical dynamics of θ- and δ-bursts arise from a balanced interplay of LC and VLPO, which maintains brain tuning to criticality across the sleep-wake cycle-a non-equilibrium behavior in sleep micro-architecture at short timescales that coexists with large-scale sleep-wake homeostasis.

Efficient NIRCam Selection of Quiescent Galaxies at 3 < z < 6 in CEERS

Substantial populations of massive quiescent galaxies at z ≥ 3 challenge our understanding of rapid galaxy growth and quenching over short timescales. In order to piece together this evolutionary puzzle, more statistical samples of these objects are required. Established techniques for identifying massive quiescent galaxies are increasingly inefficient and unconstrained at z > 3. As a result, studies report that as much as 70% of quiescent galaxies at z > 3 may be missed from existing surveys. In this work, we propose a new empirical color selection technique designed to select massive quiescent galaxies at 3 ≲ z ≲ 6 using JWST NIRCam imaging data. We use empirically constrained galaxy spectral energy distribution (SED) templates to define a region in the F277W − F444W versus F150W − F277W color plane that captures quiescent galaxies at z > 3. We apply these color selection criteria to the Cosmic Evolution Early Release Science (CEERS) Survey and use SED fitting on sources in the region to identify 44 candidate z ≳ 3 quiescent galaxies. Over half of these sources are newly discovered and, on average, exhibit specific star formation rates of poststarburst galaxies. Most of these sources would not be discovered using canonical UVJ diagrams. We derive volume density estimates of n ∼ 1–4 × 10−5 Mpc−3 at 3 < z < 5, finding excellent agreement with existing reports on similar populations in the CEERS field. Thanks to NIRCam’s wavelength coverage and sensitivity, this technique provides an efficient tool to search for large samples of these rare galaxies.

Catchment-scale assessment of drought impact on environmental flow in the Indus Basin, Pakistan

Abstract. The impact of drought on environmental flow (EF) in 27 catchments of the Indus Basin is studied from 1980–2018 using indicators of hydrologic alterations (IHAs). The standardized precipitation evapotranspiration index (SPEI) was systematically propagated from one catchment to another using principal component analysis (PCA). Threshold regression is used to determine the severity of drought (scenario 1, drought severity that causes low flows) and the month (scenario 2, months where drought has resulted in low flows) that trigger low flows in the Indus Basin. The impact of drought on low EFs is quantified using range of variability analysis (RVA), which is an integrated component of the IHA used to study the hydrological alterations in environmental flow components (EFCs) by comparing the pre- and post-impact periods of human and/or climate interventions in EFCs. The hydrological alteration factor (HAF) is calculated for each catchment in the Indus Basin. The results show that most of the catchments were vulnerable to drought during the periods of 1984 to 1986, 1991/1992, 1997 to 2003, 2007 to 2008, 2012 to 2013, and 2017 to 2018. On a longer timescale (SPEI-12), drought is more severe in the lower Indus Basin (LIB) than in the upper Indus Basin (UIB). The IHA pointed out that drought significantly impacts the distribution of EFCs, particularly extremely low flow (ELF) and low flow (LF). The magnitude and frequency of the ELF and LF events increase as drought severity increases. The threshold regression provided useful insights, indicating that moderate drought can trigger ELF and LF at shorter timescales (SPEI-1 and SPEI-6) in the UIB and middle Indus Basin (MIB). Conversely, severe and extreme droughts trigger ELF and LF at longer timescales (SPEI-12) in the LIB. The threshold regression also divided the entire study period (1980–2018) into different time periods (scenario 2), which is useful for quantifying the impact of drought on low EFs using the SPEI coefficient. Higher SPEI coefficients are observed in the LIB, indicating high alterations in EF due to drought. HAF showed high alterations in EF in most of the catchments throughout the year except in August and September. Overall, this study provided useful insights for analysing the effects of drought on EF, especially during low flows.

The sunflower sea star reduces grazing rates of purple sea urchins dependent upon urchin starvation state

AbstractEcosystem function is maintained in part by direct species interactions, but indirect interactions and non‐consumptive effects may be of equal ecological importance. Along the west coast of North America, the recent population collapse of the predatory sunflower sea star Pycnopodia helianthoides has been implicated in the proliferation of the purple sea urchin Strongylocentrotus purpuratus, and a concurrent decline in kelp canopy cover in several locales. Recent work began to quantify the predation rates effects (i.e., direct consumptive effects) of Pycnopodia on sea urchins that may lead to density‐mediated indirect effects on kelp. However, the importance of non‐consumptive effects on urchin behavior and the possible trait‐mediated indirect effects of Pycnopodia on kelp are not well understood. This leaves a critical gap in our knowledge about how these predators may be controlling grazer populations and, indirectly, primary production by macroalgae in nearshore habitats. We measured the non‐consumptive behavioral effects of Pycnopodia on S. purpuratus in the laboratory including grazing rates, feeding behavior, and movement of starved versus fed urchins, the latter simulating urchin metabolic conditions within urchin barrens. We found that the presence of a waterborne Pycnopodia cue reduced the grazing rate of fed urchins by 50% over short (~24 h) time scales. In contrast, starved urchins consumed kelp and did not exhibit an escape response in the presence of a Pycnopodia cue. This study highlights a trait‐mediated indirect interaction between Pycnopodia, S. purpuratus, and kelp, showing how the urchin response to a predator cue may differ based on urchin metabolic conditions or ecosystem state, and helps clarify the positive role of Pycnopodia on kelp forest health.

Seasonality of Retreat Rate of a Wave‐Exposed Marsh Edge

AbstractWave‐driven erosion of marsh boundaries is a major cause of marsh loss, but little research has captured the effect of seasonal differences on marsh‐edge retreat rates to illuminate temporal patterns of when the majority of this erosion is occurring. Using five surface models captured over a study year of a marsh with a steep escarped boundary in South San Francisco Bay, we find a pronounced seasonal signal, where rapid marsh retreat in the spring and summer is driven by a strong sea breeze but little change is found in the marsh‐edge position in the fall and winter. We found accretion in the mudflat transition region close to the marsh boundary in the calmer seasons however, suggesting intertwined morphodynamics of mudflats and the eroding marsh‐scarp. We observed large spatial heterogeneity in retreat rates within seasons, but less on longer (annual and decadal) timescales. The relationship between marsh‐edge retreat rates and properties of the wave field nearby is explored and contextualized against extant relationships, but our results speak to the difficulty in addressing spatial erosion/accretion variability on short (seasonal) timescales with simple models.

Colony context and size-dependent compensation mechanisms give rise to variations in nuclear growth trajectories.

To investigate the fundamental question of how cellular variations arise across spatiotemporal scales in a population of identical healthy cells, we focused on nuclear growth in hiPS cell colonies as a model system. We generated a 3D timelapse dataset of thousands of nuclei over multiple days, and developed open-source tools for image and data analysis and an interactive timelapse viewer for exploring quantitative features of nuclear size and shape. We performed a data-driven analysis of nuclear growth variations across timescales. We found that individual nuclear volume growth trajectories arise from short timescale variations attributable to their spatiotemporal context within the colony. We identified a strikingly time-invariant volume compensation relationship between nuclear growth duration and starting volume across the population. Notably, we discovered that inheritance plays a crucial role in determining these two key nuclear growth features while other growth features are determined by their spatiotemporal context and are not inherited.

Evaluating the effect of Multi-Scale droughts on autumn phenology of global land biomes with satellite observation

The end of the growing season (EOS), autumn phenology, is a significant indicator of vegetation health in terrestrial ecosystems. Higher frequency and intensity droughts are expected to have a greater impact on ecosystem homeostasis, and an urgent determination of the impact of temporal effects on autumn phenology is imperative to improve the understanding of ecosystem resilience and resistance and the stability of plant carbon sinks. This study aims to quantitatively assess the response of global autumn phenology to observed drought cumulative and lagged effects based on EOS and multi time-scales drought index (the Standardized Precipitation and Evapotranspiration Index, SPEI), and analyze the potential impact path of climate variables on EOS-SPEI relationship. Our results suggested that the cumulative and lagged effects of drought had a significant impact on the autumn phenology of approximately 27.00% and 48.73% of the vegetated area, respectively. The accumulated months were mostly concentrated on shorter time scales (1- to 3-month), and the lagged effect was mostly concentrated on 1 to 3 lagged months. These two effects on EOS were similar in different biomes and water availability, demonstrating that diverse biomes have different adaptation strategies to drought and the importance of water available for ecosystem drought mitigation. Precipitation and solar radiation had a direct negative impact on evaporation, whereas evaporation had a substantial directly positive impact on the intensity of drought effect on autumn phenology. The interaction between the climatic variables results in the accumulated months being directly positively regulated by thermal radiation, while the lagged months were directly positively influenced by precipitation, which indicates that the hydrothermal conditions at the onset of EOS occurrence govern the autumn phenology response to drought more than the occurrence time of EOS.

Testing MOND using the dynamics of nearby stellar streams

The stellar halo of the Milky Way is built up at least in part from debris from past mergers. The stars from these merger events define substructures in phase space, for example in the form of streams, which are groups of stars that move on similar trajectories. The nearby Helmi streams discovered more than two decades ago are a well-known example. Using 6D phase-space information from the Gaia space mission, recent work showed that the Helmi streams are split into two clumps in angular momentum space. This substructure can be explained and sustained in time if the dark matter halo of the Milky Way takes a prolate shape in the region probed by the orbits of the stars in the streams. Here, we explore the behaviour of the two clumps identified in the Helmi streams in a modified Newtonian dynamics (MOND) framework to test this alternative model of gravity. We performed orbit integrations of Helmi streams member stars in a simplified MOND model of the Milky Way and using the more sophisticated phantom of RAMSES simulation framework. We find with both approaches that the two Helmi streams clumps do not retain their identity and dissolve after merely Myr. This extremely short timescale would render the detection of two separate clumps very unlikely in MONDian gravity. The observational constraints provided by the streams, which MOND fails to reproduce in its current formulation, could potentially also be used to test other alternative gravity models.

The impact of oil shocks on green, clean, and socially responsible markets

The study employs novel empirical approaches, namely wavelet quantile correlation (WQC) and cross-quantilogram analysis, to examine the interrelationship between green bonds (GB), clean energy (GCE), socially responsible stocks (ESG), and variants of oil shocks during the period spanning from June 28th, 2013 to June 1st, 2023. Empirical findings from the WQC highlight consistent diversification benefits of GB against oil shocks across various market conditions at both short and long timescales, while the hedge property is evident only in long timescales. GCE reveals safe haven and hedge property in response to oil shocks at short and long timescales, while diversifier property exists only for long timescales. ESG stocks show safe haven property during the turbulence period. Moreover, the hedge property of these stocks against oil shocks is noted over the medium- to long-term horizon. Results from the cross-quantilogram analysis reinforce the diversifier properties of GB and GCE, along with the safe haven characteristics of ESG across various timescales and market conditions. These findings offer valuable suggestions to investors interested in investing in sustainable stocks in the context of a volatile oil market.

Genomic structural variation contributes to evolved changes in gene expression in high-altitude Tibetan sheep

Tibetan sheep were introduced to the Qinghai Tibet plateau roughly 3,000 B.P., making this species a good model for investigating genetic mechanisms of high-altitude adaptation over a relatively short timescale. Here, we characterize genomic structural variants (SVs) that distinguish Tibetan sheep from closely related, low-altitude Hu sheep, and we examine associated changes in tissue-specific gene expression. We document differentiation between the two sheep breeds in frequencies of SVs associated with genes involved in cardiac function and circulation. In Tibetan sheep, we identified high-frequency SVs in a total of 462 genes, including EPAS1, PAPSS2, and PTPRD. Single-cell RNA-Seq data and luciferase reporter assays revealed that the SVs had cis-acting effects on the expression levels of these three genes in specific tissues and cell types. In Tibetan sheep, we identified a high-frequency chromosomal inversion that exhibited modified chromatin architectures relative to the noninverted allele that predominates in Hu sheep. The inversion harbors several genes with altered expression patterns related to heart protection, brown adipocyte proliferation, angiogenesis, and DNA repair. These findings indicate that SVs represent an important source of genetic variation in gene expression and may have contributed to high-altitude adaptation in Tibetan sheep.

Combining orbital tuning and direct dating approaches to age-depth model development for Chew Bahir, Ethiopia

The directly dated RRMarch2021 age model (Roberts et al., 2021) for the ∼293 m long composite core from Chew Bahir, southern Ethiopia, has provided a valuable chronology for long-term climate changes in northeastern Africa. However, the age model has limitations on shorter time scales (less than 1–2 precession cycles), especially in the time range <20 kyr BP (kiloyears before present or thousand years before 1950) and between ∼155 and 428 kyr BP. To address those constraints we developed a partially orbitally tuned age model. A comparison with the ODP Site 967 record of the wetness index from the eastern Mediterranean, 3300 km away but connected to the Ethiopian plateau via the River Nile, suggests that the partially orbitally tuned age model offers some advantages compared to the exclusively directly dated age model, with the limitation of the reduced significance of (cross) spectral analysis results of tuned age models in cause-effect studies. The availability of this more detailed age model is a prerequisite for further detailed spatiotemporal correlations of climate variability and its potential impact on the exchange of different populations of Homo sapiens in the region.

Basin modelling workflow applied to the screening of deep aquifers for potential CO 2 storage

The temporal and spatial scale of interest of CO 2 storage studies lies in between reservoir and basin models. While reservoir modelling software is best fitted to address some of the multiphysics issues related to the behaviour of CO 2 once injected into the subsurface (adsorption, dissolution, near injection wellbore mechanics and temperature, and, in some cases, fluid rock interaction) within a human timescale, basin modelling tools handle better the full basin volume and time-scale heterogeneities that impact the storage potential and risk associated with CO 2 injection. This study takes a basin modelling approach to provide an assessment of the influence of geological evolution on CO 2 storage capacity, both at the reservoir level, by helping to estimate the amount of CO 2 that can be stored in its connected porosity, and at the cap-rock level, by assessing the seal integrity. Our basin model also captures the evolution of the pressure plume induced by the CO 2 injection, taking into account the pressure and temperature fields, aquifer connectivity and permeability, and seal integrity, on a much shorter timescale than is usually considered by such a model. The results show the impact of basin evolution on aquifer properties and consequently on the dissipation of the induced pressure plume. They also highlight the large-scale influence of the CO 2 on the pressure field both vertically along the stratigraphic column, when the pressure plume reaches shallower aquifers through unconformities, and horizontally, when good aquifer injectivity and connectivity allows the pressure plume to dissipate widely.

Reversions mask the contribution of adaptive evolution in microbiomes.

When examining bacterial genomes for evidence of past selection, the results obtained depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed by , the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale-dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with exactly opposite implications for dynamical intuition and applications of . Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain the decay given only dozens of locally-fluctuating selective pressures, which is realistic in the context of Bacteroides genomes. The success of the adaptive reversion model argues for interpreting low values of obtained from long-time scales with caution, as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short time scales.

Photon correlations in the collective emission of hybrid gold-(CdSe/CdS/CdZnS) nanocrystal supraparticles

We investigate the photon statistics of the light emitted by single self-assembled hybrid gold-CdSe/CdS/CdZnS colloidal nanocrystal supraparticles through the detailed analysis of the intensity autocorrelation function g (2)(τ). We first reveal that, despite the large number of nanocrystals involved in the supraparticle emission, antibunching can be observed. We then present a model based on non-coherent Förster energy transfer and Auger recombination that well captures photon antibunching. Finally, we demonstrate that some supraparticles exhibit a bunching effect at short time scales corresponding to coherent collective emission.